Prof Graham Williams

Research output

Research output per year 2001 2005 2006 2008 2009 2012 2014 2021 2021

• 12 Conference contribution
• 10 Article
• 1 Edited Book
• 1 Commissioned report
• 5 More
  • 1 Paper
  • 1 Comment/debate
  • 1 Conference article
  • 1 Editorial
  • 1 Review article

Research output per year

Research output per year

Search results

• 2014

  Extensions to quantile regression forests for very high-dimensional data

  Tung, N. T., Huang, J. Z., Khan, I., Li, M. J. & Williams, G., 2014, In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 8444 LNAI, PART 2, p. 247-258 12 p.

  Research output: Contribution to journal › Conference article › peer-review

  • High Dimensional Data 100%
  • Random Decision Forest 100%
  • Set Partition 25%
  • Prediction Value 25%
  8 Citations (Scopus)